Differences in timing control processes between tapping and circle drawing have been extensively documented during continuation timing. Differences between event and emergent control processes have also been documented for synchronization timing using emergent tasks that have minimal event-related information. However, it is not known whether the original circle-drawing task also behaves differently than tapping during synchronization. In this experiment, 10 participants performed a table-tapping and a continuous circle-drawing task to an auditory metronome. Synchronization performance was assessed via the value and variability of asynchronies. Synchronization was substantially more difficult in circle drawing than in tapping. Participants drawing timed circles exhibited drift in synchronization error and did not maintain a consistent phase relationship with the metronome. An analysis of temporal anchoring revealed that timing to the timing target was not more accurate than timing to other locations on the circle trajectory. The authors conclude that participants were not able to synchronize movement with metronome tones in the circle-drawing task despite other findings that cyclical tasks do exhibit auditory motor synchronization, because the circle-drawing task is unique and absent of event and cycle position information.
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http://dx.doi.org/10.1080/00222895.2011.555796 | DOI Listing |
Behav Sci (Basel)
November 2024
Department of Human Movement Sciences, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands.
Childhood is an obvious period for motor learning, since children's musculoskeletal and nervous systems are still in development. Adults adapt movements based on reward feedback about success and failure, but it is less established whether school-age children also exhibit such reward-based motor learning. We designed a new 'circle-drawing' task suitable for assessing reward-based motor learning in both children (7-17 years old) and adults (18-65 years old).
View Article and Find Full Text PDFPsych J
December 2024
Academic Division of Olympic Sports, Beijing Sport University, Beijing, China.
The current study aimed to investigate the impact of recreational gymnastics on executive function in Chinese preschoolers, with a focus on gymnastics potential to enhance core components of executive function. A total of 63 preschool children who received full-time education were randomly assigned to either an intervention group (N = 31, mean age = 66.27 months, SD = 3.
View Article and Find Full Text PDFAppl Neuropsychol Child
May 2024
Special Education Department, Faculty of Education, Imam Muhammad bin Saud University, Saudi Arabia.
The present study was conducted with the aim of investigating the effect of exergames in improving the motor memory and inhibitory control of children with executive functions disorder. Children, selected by simple random method were divided into two groups: experimental (n = 16) and control (n = 16). Circle drawing task, and The Serial Reaction Time Task were used to collect and analyze data.
View Article and Find Full Text PDFFront Integr Neurosci
April 2024
Music and Health Science Research Collaboratory, University of Toronto, Faculty of Music, Toronto, ON, Canada.
Introduction: Autistic individuals demonstrate greater variability and timing error in their motor performance than neurotypical individuals, likely due at least in part to atypical cerebellar characteristics and connectivity. These motor difficulties may differentially affect discrete as opposed to continuous movements in autistic individuals. Augmented auditory feedback has the potential to aid motor timing and variability due to intact auditory-motor pathways in autism and high sensitivity in autistic individuals to auditory stimuli.
View Article and Find Full Text PDFSci Rep
March 2024
Pacific Parkinson's Research Centre, University of British Columbia, Vancouver, Canada.
This study introduces PDMotion, a mobile application comprising 11 digital tests, including those adapted from the MDS-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III and novel assessments, for remote Parkinson's Disease (PD) motor symptoms evaluation. Employing machine learning techniques on data from 50 PD patients and 29 healthy controls, PDMotion achieves accuracies of 0.878 for PD status prediction and 0.
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